<p> At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what's next.<br /> <br /> In April 2022, we introduced a new, more affordable, ad-supported tier for our customers, marking a significant milestone for Netflix. Our focus is now on expanding choices for consumers and providing advertisers with a premium TV brand experience that surpasses traditional linear formats. The challenge ahead involves scaling our ad tech to maximize its impact on our business.<br /> <br /> The Ad Marketplace team in Ads Data Science and Engineering plays a crucial role in Netflix's ad business growth. The mission for this team is to build a healthy, competitive, and innovative ad marketplace that balances long term Netflix revenue, member experience, and advertiser outcomes. As an important part of the Ad Marketplace team, the Member Ad Experience team is responsible for understanding the impact of delivery policy and decisioning to member experience, including ad load, ad frequency cap, ad insertion, and podding optimization. The team builds causal inference and predictive models to quantify such impact to members, and use them in ad delivery optimization. Our goal is to create a best-in-class member ad experience through responsible monetization that prioritizes long-term growth. As a leader in this domain, you will collaborate closely with Product and Engineering partner teams to think expansively about our business goals and define the blueprint for achieving them through models and algorithms. Your team will apply rigorous analytical methods to evaluate concepts, dissect challenges, build models and workflows, provide recommendations, and drive success on end-to-end initiatives in this nascent (0 - 1) space.<br /> <br /> Responsibilities<br /> • Hire, inspire, and grow high-performing Machine Learning Scientists, Data Scientists, and Analytics Engineers.<br /> • Lead strong partnerships with stakeholders from across the business - from product management, engineering, consumer insights, content, and strategy.<br /> • Instill an inclusive culture that is innovative and collaborative, both within your team and in the broader organization.<br /> • Develop a team charter and roadmap that optimizes the impact of the team and reflects evolving business needs.<br /> • Act as an ambassador between the Product, Engineering, Strategy, and DSE teams by having a deep knowledge of how the Netflix Ads product works.<br /> • Ensure that your team is producing consistently trustworthy and high-quality technical outputs that influence & impact the business.<br /> <br /> The Ideal Candidate:<br /> • Demonstrated tenacity, resilience, and leadership experience that enables you to organize and drive cross-functional projects, overcome challenges, and propose solutions.<br /> • Be both quantitative and qualitative. You should be able to quickly assess and understand complex systems, but also have high EQ, so that you can be a product ambassador to the rest of the organization.<br /> • You are a player-coach. You can develop roadmaps and strategy, but also execute on technical work and ensure that your team produces consistent high quality outputs.<br /> • Superb communication skills - You must be able to cultivate strong working relationships, communicate effectively, write meticulously, and give outstanding presentations to both technical and creative audiences.<br /> • Experience building and leading hybrid Data Science and ML teams in the Ads space.<br /> • Capacity and passion to translate business objectives into actionable analyses, and use analytics to guide product and business with quantitative recommendations.<br /> • A passion for TV and movies and defining the future of entertainment.<br /> <br /> Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $523,000.00 - $920,000.00. This compensation range will vary based on location.<br /> <br /> Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here .<br /> <br /> Netflix is a unique culture and environment. Learn more here .<br /> <br /> Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.<br /> <br /> We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.<br /> <br /> Job is open for no less than 7 days and will be removed when the position is filled.<br /> <p id='jobcode'>Jobcode: Reference SBJ-869m5k-172-68-70-24-42 in your application.</p> </p>